Skip to content

GitLab

Commit e72c0c43 authored by carlushuang's avatar carlushuang
Browse files

Merge remote-tracking branch 'origin/develop' into cpu_avx2

parents d714fa15 313bbea5
Hide whitespace changes
Inline Side-by-side
Showing with 127 additions and 38 deletions
test/reference_conv_fwd/reference_conv_fwd.cpp
View file @ e72c0c43
......@@ -23,11 +23,16 @@ template <typename T>
struct FillMonotonicSeq
{
T m_init_value{0};
T m_step{1};
template <typename ForwardIter>
void operator()(ForwardIter first, ForwardIter last) const
{
std::iota(first, last, m_init_value);
std::generate(first, last, [=, n = m_init_value]() mutable {
auto tmp = n;
n += m_step;
return tmp;
});
}
};
......@@ -53,7 +58,7 @@ template <ck::index_t NDim,
typename FillInputOp = FillMonotonicSeq<InDataType>,
typename FillWeightsOp = FillConstant<WeiDataType>>
Tensor<OutDataType> RunReferenceConv(const ck::conv_util::ConvParams& params,
const FillInputOp& fill_input_op = FillInputOp{0},
const FillInputOp& fill_input_op = FillInputOp{},
const FillWeightsOp& fill_weights_op = FillWeightsOp{0.5f})
{
std::vector<std::size_t> input_dims{static_cast<std::size_t>(params.N),
......@@ -84,6 +89,9 @@ Tensor<OutDataType> RunReferenceConv(const ck::conv_util::ConvParams& params,
fill_weights_op(weights.begin(), weights.end());
std::fill(host_output.begin(), host_output.end(), OutDataType(0.f));
// std::cout <<"input: " << input.mDesc << std::endl << input.mData << std::endl;
// std::cout <<"weight: " << weights.mDesc << std::endl << weights.mData << std::endl;
auto ref_conv = ck::tensor_operation::host::ReferenceConvFwd<InDataType,
WeiDataType,
OutDataType,
......@@ -104,6 +112,7 @@ Tensor<OutDataType> RunReferenceConv(const ck::conv_util::ConvParams& params,
OutElementOp{});
ref_invoker.Run(ref_argument);
// std::cout <<"output: " << host_output.mDesc << std::endl << host_output.mData << std::endl;
return host_output;
}
......@@ -139,10 +148,10 @@ bool TestConv2DNHWC()
472.5,
490.5,
508.5};
res = res && test_util::check_err(out_tensor.mDesc.GetLengths(),
ref_dims,
"Error: wrong output tensor dimensions!");
res = res && test_util::check_err(out_tensor.mData, ref_data, "Error: incorrect results!");
res = res && test::check_err(out_tensor.mDesc.GetLengths(),
ref_dims,
"Error: wrong output tensor dimensions!");
res = res && test::check_err(out_tensor.mData, ref_data, "Error: incorrect results!");
params.N = 1;
params.K = 2;
......@@ -162,10 +171,10 @@ bool TestConv2DNHWC()
747., 747., 1138.5, 1138.5, 1174.5, 1174.5, 1210.5, 1210.5, 1246.5, 1246.5,
1035., 1035., 1570.5, 1570.5, 1606.5, 1606.5, 1642.5, 1642.5, 1678.5, 1678.5,
1323., 1323., 2002.5, 2002.5, 2038.5, 2038.5, 2074.5, 2074.5, 2110.5, 2110.5};
res = res && test_util::check_err(out_tensor.mDesc.GetLengths(),
ref_dims,
"Error: wrong output tensor dimensions!");
res = res && test_util::check_err(out_tensor.mData, ref_data, "Error: incorrect results!");
res = res && test::check_err(out_tensor.mDesc.GetLengths(),
ref_dims,
"Error: wrong output tensor dimensions!");
res = res && test::check_err(out_tensor.mData, ref_data, "Error: incorrect results!");
return res;
}
......@@ -194,10 +203,10 @@ bool TestConv1DNWC()
ck::tensor_layout::convolution::NWK>(params);
std::vector<std::size_t> ref_dims{1, 1, 4};
std::vector<float> ref_data{7.5, 13.5, 19.5, 25.5};
res = res && test_util::check_err(out_tensor.mDesc.GetLengths(),
ref_dims,
"Error: wrong output tensor dimensions!");
res = res && test_util::check_err(out_tensor.mData, ref_data, "Error: incorrect results!");
res = res && test::check_err(out_tensor.mDesc.GetLengths(),
ref_dims,
"Error: wrong output tensor dimensions!");
res = res && test::check_err(out_tensor.mData, ref_data, "Error: incorrect results!");
params.num_dim_spatial = 1;
params.N = 1;
......@@ -219,10 +228,10 @@ bool TestConv1DNWC()
ck::tensor_layout::convolution::NWK>(params);
ref_dims = std::vector<std::size_t>{1, 2, 5};
ref_data = std::vector<float>{9., 9., 19.5, 19.5, 31.5, 31.5, 43.5, 43.5, 55.5, 55.5};
res = res && test_util::check_err(out_tensor.mDesc.GetLengths(),
ref_dims,
"Error: wrong output tensor dimensions!");
res = res && test_util::check_err(out_tensor.mData, ref_data, "Error: incorrect results!");
res = res && test::check_err(out_tensor.mDesc.GetLengths(),
ref_dims,
"Error: wrong output tensor dimensions!");
res = res && test::check_err(out_tensor.mData, ref_data, "Error: incorrect results!");
params.num_dim_spatial = 1;
params.N = 2;
......@@ -235,16 +244,14 @@ bool TestConv1DNWC()
params.input_left_pads = std::vector<ck::index_t>{1};
params.input_right_pads = std::vector<ck::index_t>{1};
auto out_tensor2 =
RunReferenceConv<1,
float,
float,
float,
ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK>(params, [](auto first, auto last) {
std::generate(first, last, [n = 0]() mutable { return float(n++) * float(0.1f); });
});
auto out_tensor2 = RunReferenceConv<1,
float,
float,
float,
ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK>(
params, FillMonotonicSeq<float>{0.f, 0.1f});
ref_dims = std::vector<std::size_t>{2, 16, 16};
ref_data = std::vector<float>{
......@@ -312,10 +319,94 @@ bool TestConv1DNWC()
72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9,
49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4,
49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4};
res = res && test_util::check_err(out_tensor2.mDesc.GetLengths(),
ref_dims,
"Error: wrong output tensor dimensions!");
res = res && test_util::check_err(out_tensor2.mData, ref_data, "Error: incorrect results!");
res = res && test::check_err(out_tensor2.mDesc.GetLengths(),
ref_dims,
"Error: wrong output tensor dimensions!");
res = res && test::check_err(out_tensor2.mData, ref_data, "Error: incorrect results!");
return res;
}
bool TestConv3DNCDHW()
{
bool res{true};
ck::conv_util::ConvParams params;
params.num_dim_spatial = 3;
params.N = 1;
params.K = 1;
params.C = 2;
params.filter_spatial_lengths = std::vector<ck::index_t>{3, 3, 3};
params.input_spatial_lengths = std::vector<ck::index_t>{6, 6, 6};
params.conv_filter_strides = std::vector<ck::index_t>{1, 1, 1};
params.conv_filter_dilations = std::vector<ck::index_t>{1, 1, 1};
params.input_left_pads = std::vector<ck::index_t>{0, 0, 0};
params.input_right_pads = std::vector<ck::index_t>{0, 0, 0};
auto out_tensor = RunReferenceConv<3,
float,
float,
float,
ck::tensor_layout::convolution::NCDHW,
ck::tensor_layout::convolution::KCZYX,
ck::tensor_layout::convolution::NKDHW>(
params, FillMonotonicSeq<float>{0.f, 0.1f});
std::vector<std::size_t> ref_dims{1, 1, 4, 4, 4};
std::vector<float> ref_data{
407.7, 410.40002, 413.09998, 415.80002, 423.90002, 426.6, 429.30002, 432.,
440.1, 442.80002, 445.5, 448.2, 456.30002, 459., 461.7, 464.40002,
504.90002, 507.6, 510.30002, 513., 521.1, 523.8, 526.5, 529.2001,
537.3, 540., 542.7001, 545.4, 553.5, 556.2001, 558.9, 561.6,
602.10004, 604.8, 607.5, 610.2, 618.3, 621., 623.7, 626.4,
634.5, 637.2, 639.9, 642.60004, 650.7, 653.4, 656.10004, 658.8,
699.3, 702., 704.7, 707.4, 715.5, 718.2, 720.9, 723.60004,
731.7, 734.4001, 737.10004, 739.8, 747.9001, 750.60004, 753.3, 756.};
res = res && test::check_err(out_tensor.mDesc.GetLengths(),
ref_dims,
"Error [case 1]: wrong output tensor dimensions!");
res = res && test::check_err(out_tensor.mData, ref_data, "Error [case 1]: incorrect results!");
params.N = 1;
params.K = 2;
params.C = 2;
params.filter_spatial_lengths = std::vector<ck::index_t>{3, 3, 3};
params.input_spatial_lengths = std::vector<ck::index_t>{12, 12, 12};
params.conv_filter_strides = std::vector<ck::index_t>{3, 3, 3};
params.conv_filter_dilations = std::vector<ck::index_t>{1, 1, 1};
params.input_left_pads = std::vector<ck::index_t>{0, 0, 0};
params.input_right_pads = std::vector<ck::index_t>{0, 0, 0};
out_tensor = RunReferenceConv<3,
float,
float,
float,
ck::tensor_layout::convolution::NCDHW,
ck::tensor_layout::convolution::KCZYX,
ck::tensor_layout::convolution::NKDHW>(
params, FillMonotonicSeq<float>{0.f, 0.1f});
ref_dims = std::vector<std::size_t>{1, 2, 4, 4, 4};
ref_data = std::vector<float>{
2756.7002, 2764.7998, 2772.9001, 2781., 2853.9001, 2862., 2870.1, 2878.2002,
2951.1, 2959.2002, 2967.2998, 2975.4001, 3048.2998, 3056.4001, 3064.5, 3072.6,
3923.1, 3931.2, 3939.2998, 3947.4, 4020.2998, 4028.4001, 4036.5002, 4044.5999,
4117.5, 4125.6, 4133.7, 4141.8, 4214.7, 4222.8, 4230.9004, 4239.,
5089.5, 5097.5996, 5105.7, 5113.8, 5186.7, 5194.8, 5202.9, 5211.,
5283.9004, 5292., 5300.0996, 5308.2, 5381.0996, 5389.2, 5397.3, 5405.4004,
6255.9004, 6264.0005, 6272.1, 6280.2, 6353.1, 6361.2, 6369.301, 6377.4,
6450.301, 6458.4, 6466.5, 6474.6, 6547.5, 6555.6, 6563.699, 6571.801,
2756.7002, 2764.7998, 2772.9001, 2781., 2853.9001, 2862., 2870.1, 2878.2002,
2951.1, 2959.2002, 2967.2998, 2975.4001, 3048.2998, 3056.4001, 3064.5, 3072.6,
3923.1, 3931.2, 3939.2998, 3947.4, 4020.2998, 4028.4001, 4036.5002, 4044.5999,
4117.5, 4125.6, 4133.7, 4141.8, 4214.7, 4222.8, 4230.9004, 4239.,
5089.5, 5097.5996, 5105.7, 5113.8, 5186.7, 5194.8, 5202.9, 5211.,
5283.9004, 5292., 5300.0996, 5308.2, 5381.0996, 5389.2, 5397.3, 5405.4004,
6255.9004, 6264.0005, 6272.1, 6280.2, 6353.1, 6361.2, 6369.301, 6377.4,
6450.301, 6458.4, 6466.5, 6474.6, 6547.5, 6555.6, 6563.699, 6571.801};
res = res && test::check_err(out_tensor.mDesc.GetLengths(),
ref_dims,
"Error [case 2]: wrong output tensor dimensions!");
res =
res && test::check_err(
out_tensor.mData, ref_data, "Error [case 2]: incorrect results!", 1e-4f, 1e-6f);
return res;
}
......@@ -329,5 +420,7 @@ int main(void)
std::cout << "TestConv2DNHWC ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
res = TestConv1DNWC();
std::cout << "TestConv1DNHWC ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
res = TestConv3DNCDHW();
std::cout << "TestConv3DNCDHW ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
return 0;
}
test/space_filling_curve/space_filling_curve.cpp
View file @ e72c0c43
......@@ -14,12 +14,8 @@ int main(int argc, char** argv)
(void)argc;
(void)argv;
{
traverse_using_space_filling_curve();
auto err = hipDeviceSynchronize();
(void)err;
assert(err == hipSuccess);
}
traverse_using_space_filling_curve();
return 0;
}
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment